A novel approach to potato processing using intelligent data analytics and advanced control

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In the manufacturer of food in the food industry, there are rigid operational standards and processing methodologies that have to be adhered to. In many instances, these operations and processing methods demand that they are well controlled within tight tolerances. The processing of the raw potatoes to a wide variety of products is just one example. McCain Foods in Florenceville, NB, Canada since 1957 as a company has been committed itself to be continuously improving and applying new technologies to its production of nearly one-third of the French fried potatoes in the world. This project focuses on conducting research in order to enhance the potato peeling process, which is key to overall efficiency of the production of potato fries. Currently, the peeling process involves using steam at high flows entering a rotating vessel that contains the raw material for a defined period of time. The optimal time for steaming is not known at this point as well as the vessel's rotating speed. Other parameters influence the peeling process such as the potato dimensionality and type. As the steaming process is key to the peeling of the raw potato, the company is keen on improving this initial process for minimizing energy consumption and maximizing peeling efficiency. Over steaming or under steaming can result in poor peeling, translating to millions of dollars annually in lost revenue. The research would involve several researchers conducting sequential and concurrent tasks that include the following: (a) formulating from first principles an analytical model of the overall potato peeling mechanism, (b) conducting various experiments to formulate nonlinear time series models, (c) integrating high resolution thermal imaging cameras that provide thermal signatures of the raw material during steaming and after, (c) using the thermal data to enhance these time series models in realtime, and (d) developing an intelligent controller that uses this information (thermal and many others) to make optimal actions to the several actuators (valves, heaters, motors etc.). McCain Foods will be providing $50,000 in cash as well as $54,400 inkind support on this project. The project has a timeline of 2 years.